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A common classifier for unlabeled nodes on undirected graphs uses label propagation from the labeled nodes, equivalent to the harmonic predictor on Gaussian random fields (GRFs). For active learning on GRFs, the commonly used V-optimality criterion queries nodes that reduce the L 2 (regression) loss. V-optimality satisfies a submodularity property showing that greedy reduction produces a (1 − 1/e) globally optimal solution. However, L 2 loss may not characterise the true nature of 0/1 loss indblp:conf/nips/MaGS13 fatcat:ts42pggfobbw3acnqq7qznwpvm